Why is dot product attention faster than additive attention?
The additive attention method that the researchers are comparing to corresponds to a neural network with 3 layers (it is not actually straight addition). Computing this will involve one multiplication of the input vector by a matrix, then by another matrix, and then the computation of something like a softmax. Smart implementation of a dot-product will not break out the whole matrix multiplication algorithm for it, and it will basically be a tight, easily parallelized loop.